Application of Machine Learning Models to the Analysis of Skid Resistance Data
This paper evaluates the ability of some state-of-the-art Machine Learning models, namely SVM (support vector machines), DT (decision tree) and MLR (multiple linear regression), to predict pavement skid resistance. The study encompasses both regression and classification tasks. In the regression tas...
Main Authors: | Aboubakar Koné, Ahmed Es-Sabar, Minh-Tan Do |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-08-01
|
Series: | Lubricants |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-4442/11/8/328 |
Similar Items
-
Performance Evaluation of Electric Vehicle Model under Skid Control Technique
by: Nevin Fawzy, et al.
Published: (2021-06-01) -
Re-Evaluating the Risk of Using Higher-Skid-Resistance Aggregates
by: David Woodward, et al.
Published: (2023-07-01) -
Analysis of skid resistance of road pavements in the initial period of its life
by: Marta Wasilewska
Published: (2014-12-01) -
The effect of wood species on the anti-skid resistance of coatings
by: Isabel Fernández, et al.
Published: (2014-12-01) -
The Effects of Angularity Number on Texture Depths and Skid Resistance of Stone Mastic Asphalt
by: Musa, Mohtady Ali
Published: (2002)